Using Hydrogen Isotopes to Assign Origins of Bats in the Eastern United States
Bibliographic record
Abstract
Stable hydrogen isotopes (δDs) in metabolically inert tissues such as feathers and hair provide a set of endogenous markers that may be useful for establishing migratory connectivity in animals. We tested the assumption of a clear relationship between δD values of growing-season-weighted average precipitation (δDp) derived from 2 geographic information system (GIS) models or latitude (LAT) and δD values in bat hair (δDh), and examined intra- and interspecific variation in δDh of 4 bat species in the eastern United States. We analyzed 251 hair samples from 1 long-distance migrant (eastern red bat [Lasiurus borealis]) and 3 regional migrants (Indiana bat [Myotis sodalis], northern long-eared bat [M. septentrionalis], and little brown bat [M. lucifugus]) captured during the reproductive period (pregnancy and lactation) when bats are resident. LAT explained more of the variation in δDh than δDp derived from either of the GIS-based models, although 1 model of δDp performed better for some species. We found significant intraspecific differences in the relationships between δDh and LAT and between δDh and estimates of δDp derived from Bowen et al. (δDpB) for L. borealis, and significant variation in the regression equations of δDh and LAT and δDh and δDp among species for adult females and adult males. Stable hydrogen isotope analysis may be a valuable tool for studying migratory connectivity in bats, but significant intra- and interspecific variation in δDh values suggests that pooling across sex and age categories and use of surrogate species should be avoided.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".